The ability of GPT-3 and its "cousins" to generate texts for a broad range of tasks–from summarization to question-answering and information retrieval—via an intuitive natural language interface—may hold great promise for social science research. Already, researchers are using GPT-3 for tasks ranging from optical character recognition (OCR) correction to open-ended survey response measurement.

This session reviews what LLMs are, how they work, what they can do, and what the implications are of using these tools in academic social science research. There will also be a hands-on portion using OpenAI tools and supplementary libraries. 

Participants who want to code along to the hands-on portion should be familiar with Python and must have an OpenAI account prior to the workshop. Please RSVP.